Identification of biomarkers for genotyping <Emphasis Type="Italic">Aspergilli</Emphasis> using non-linear methods for clustering and classification

Background  

In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinantAspergillus nidulans(mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.     

Improving the <Emphasis Type="Italic">i</Emphasis>MM904 <Emphasis Type="Italic">S. cerevisiae</Emphasis> metabolic model using essentiality and synthetic lethality data

Background  

Saccharomyces cerevisiae is the first eukaryotic organism for which a multi-compartment genome-scale metabolic model was constructed. Since then a sequence of improved metabolic reconstructions for yeast has been introduced. These metabolic models have been extensively used to elucidate the organizational principles of yeast metabolism and drive yeast strain engineering strategies for targeted overproductions. They have also served as a starting point and a benchmark for the reconstruction of genome-scale metabolic models for other eukaryotic organisms. In spite of the successive improvements in the details of the described metabolic processes, even the recent yeast model (i.e., i MM904) remains significantly less predictive than the latest E. coli model (i.e., i AF1260). This is manifested by its significantly lower specificity in predicting the outcome of grow/no grow experiments in comparison to the E. coli model.     

Genotype networks,innovation, and robustness in sulfur metabolism

Background  

A metabolism is a complex network of chemical reactions. This network synthesizes multiple small precursor molecules of biomass from chemicals that occur in the environment. The metabolic network of any one organism is encoded by a metabolic genotype, defined as the set of enzyme-coding genes whose products catalyze the network's reactions. Each metabolic genotype has a metabolic phenotype. We define this metabolic phenotype as the spectrum of different sources of a chemical element that a metabolism can use to synthesize biomass. We here focus on the element sulfur. We study properties of the space of all possible metabolic genotypes in sulfur metabolism by analyzing random metabolic genotypes that are viable on different numbers of sulfur sources.     

Characterization of oxylipins and dioxygenase genes in the asexual fungus Aspergillus niger

Background  

Aspergillus niger is an ascomycetous fungus that is known to reproduce through asexual spores, only. Interestingly, recent genome analysis of A. niger has revealed the presence of a full complement of functional genes related to sexual reproduction [1]. An example of such genes are the dioxygenase genes which in Aspergillus nidulans, have been shown to be connected to oxylipin production and regulation of both sexual and asexual sporulation [2–4]. Nevertheless, the presence of sex related genes alone does not confirm sexual sporulation in A. niger.     

Low degree metabolites explain essential reactions and enhance modularity in biological networks

Background  

Recently there has been a lot of interest in identifying modules at the level of genetic and metabolic networks of organisms, as well as in identifying single genes and reactions that are essential for the organism. A goal of computational and systems biology is to go beyond identification towards an explanation of specific modules and essential genes and reactions in terms of specific structural or evolutionary constraints.     

Estimating the size of the solution space of metabolic networks

Background  

Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network is quite well understood there is still a lack of comprehension regarding the global functional behavior of the system. In the last few years flux-balance analysis (FBA) has been the most successful and widely used technique for studying metabolism at system level. This method strongly relies on the hypothesis that the organism maximizes an objective function. However only under very specific biological conditions (e.g. maximization of biomass for E. coli in reach nutrient medium) the cell seems to obey such optimization law. A more refined analysis not assuming extremization remains an elusive task for large metabolic systems due to algorithmic limitations.     

Metabolic engineering of a reduced-genome strain of Escherichia coli for L-threonine production

Background  

Deletion of large blocks of nonessential genes that are not needed for metabolic pathways of interest can reduce the production of unwanted by-products, increase genome stability, and streamline metabolism without physiological compromise. Researchers have recently constructed a reduced-genome Escherichia coli strain MDS42 that lacks 14.3% of its chromosome.     

Genome-wide metabolic re-annotation of Ashbya gossypii: new insights into its metabolism through a comparative analysis with Saccharomyces cerevisiae and Kluyveromyces lactis

Background

Ashbya gossypii is an industrially relevant microorganism traditionally used for riboflavin production. Despite the high gene homology and gene order conservation comparatively with Saccharomyces cerevisiae, it presents a lower level of genomic complexity. Its type of growth, placing it among filamentous fungi, questions how close it really is from the budding yeast, namely in terms of metabolism, therefore raising the need for an extensive and thorough study of its entire metabolism. This work reports the first manual enzymatic genome-wide re-annotation of A. gossypii as well as the first annotation of membrane transport proteins.

Results

After applying a developed enzymatic re-annotation pipeline, 847 genes were assigned with metabolic functions. Comparatively to KEGG’s annotation, these data corrected the function for 14% of the common genes and increased the information for 52 genes, either completing existing partial EC numbers or adding new ones. Furthermore, 22 unreported enzymatic functions were found, corresponding to a significant increase in the knowledge of the metabolism of this organism. The information retrieved from the metabolic re-annotation and transport annotation was used for a comprehensive analysis of A. gossypii’s metabolism in comparison to the one of S. cerevisiae (post-WGD – whole genome duplication) and Kluyveromyces lactis (pre-WGD), suggesting some relevant differences in several parts of their metabolism, with the majority being found for the metabolism of purines, pyrimidines, nitrogen and lipids. A considerable number of enzymes were found exclusively in A. gossypii comparatively with K. lactis (90) and S. cerevisiae (13). In a similar way, 176 and 123 enzymatic functions were absent on A. gossypii comparatively to K. lactis and S. cerevisiae, respectively, confirming some of the well-known phenotypes of this organism.

Conclusions

This high quality metabolic re-annotation, together with the first membrane transporters annotation and the metabolic comparative analysis, represents a new important tool for the study and better understanding of A. gossypii’s metabolism.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-810) contains supplementary material, which is available to authorized users.     

Structural correlations in bacterial metabolic networks

Background  

Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution.     

Identifying metabolic enzymes with multiple types of association evidence

Background  

Existing large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes.     

Effect of temperature up-shift on fermentation and metabolic characteristics in view of gene expressions in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background  

Escherichia coli induces heat shock genes to the temperature up-shift, and changes the metabolism by complicated mechanism. The heat shock response is of practical importance for the variety of applications such as temperature-induced heterologous protein production, simultaneous saccharification and fermentation (SSF) etc. However, the effect of heat shock on the metabolic regulation is not well investigated. It is strongly desired to understand the metabolic changes and its mechanism upon heat shock in practice for the efficient metabolite production by temperature up-shift. In the present research, therefore, we investigated the effect of temperature up-shift from 37°C to 42°C on the metabolism in view of gene expressions.     

<Emphasis Type="Italic">atonal</Emphasis>- and <Emphasis Type="Italic">achaete-scute</Emphasis>-related genes in the annelid <Emphasis Type="Italic">Platynereis dumerilii</Emphasis>: insights into the evolution of neural basic-Helix-Loop-Helix genes

Background  

Functional studies in model organisms, such as vertebrates and Drosophila, have shown that basic Helix-loop-Helix (bHLH) proteins have important roles in different steps of neurogenesis, from the acquisition of neural fate to the differentiation into specific neural cell types. However, these studies highlighted many differences in the expression and function of orthologous bHLH proteins during neural development between vertebrates and Drosophila. To understand how the functions of neural bHLH genes have evolved among bilaterians, we have performed a detailed study of bHLH genes during nervous system development in the polychaete annelid, Platynereis dumerilii, an organism which is evolutionary distant from both Drosophila and vertebrates.     

Expression of the peroxisome proliferator activated receptor γ gene is repressed by DNA methylation in visceral adipose tissue of mouse models of diabetes

Background  

Adipose tissues serve not only as a store for energy in the form of lipid, but also as endocrine tissues that regulates metabolic activities of the organism by secreting various kinds of hormones. Peroxisome proliferator activated receptor γ (PPARγ) is a key regulator of adipocyte differentiation that induces the expression of adipocyte-specific genes in preadipocytes and mediates their differentiation into adipocytes. Furthermore, PPARγ has an important role to maintain the physiological function of mature adipocyte by controlling expressions of various genes properly. Therefore, any reduction in amount and activity of PPARγ is linked to the pathogenesis of metabolic syndrome.     

Does the core circadian clock in the moss <Emphasis Type="Italic">Physcomitrella patens</Emphasis> (Bryophyta) comprise a single loop?

Background  

The endogenous circadian clock allows the organism to synchronize processes both to daily and seasonal changes. In plants, many metabolic processes such as photosynthesis, as well as photoperiodic responses, are under the control of a circadian clock. Comparative studies with the moss Physcomitrella patens provide the opportunity to study many aspects of land plant evolution. Here we present a comparative overview of clock-associated components and the circadian network in the moss P. patens.     

Energy metabolism of <Emphasis Type="Italic">Heliobacterium modesticaldum</Emphasis> during phototrophic and chemotrophic growth

Background  

Heliobacterium modesticaldum is a gram-positive nitrogen-fixing phototrophic bacterium that can grow either photoheterotrophically or chemotrophically but not photoautotrophically. Surprisingly, this organism is lacking only one gene for the complete reverse tricarboxylic acid (rTCA) cycle required for autotrophic carbon fixation. Along with the genomic information reported recently, we use multiple experimental approaches in this report to address questions regarding energy metabolic pathways in darkness, CO₂ fixation, sugar assimilation and acetate metabolism.